A self-coherence enhancement algorithm and its application to enhancing three-dimensional source estimation from EEGs

A Long Short-Term Memory Network for Sparse Spatiotemporal EEG Source Imaging

EEG inverse problem is underdetermined, which poses a long standing challenge in Neuroimaging. The combination of source-imaging and analysis of cortical directional networks enables us to noninvasively explore the underlying neural processes. However, existing EEG source imaging approaches mainly focus on performing the direct inverse operation for source estimation, which will be inevitably influenced by noise and the strategy used to find the inverse solution. Here, we develop a new source imaging technique, Deep Brain Neural Network (DeepBraiNNet), for robust sparse spatiotemporal EEG source estimation. In DeepBraiNNet, considering that Recurrent Neural Network (RNN) are usually "deep" in temporal dimension and thus suitable for time sequence modelling, the RNN with Long Short-Term Memory (LSTM) is utilized to approximate the inverse operation for the lead field matrix instead of performing the direct inverse operation, which avoids the possible effect of the direct inverse operation on the underdetermined lead field matrix prone to be influenced by noise. Simulations on various source patterns and noise conditions confirmed that the proposed approach could actually recover the spatiotemporal sources well, outperforming existing state of-the-art methods. DeepBraiNNet also estimated sparse MI related activation patterns when it was applied to a real Motor Imagery dataset, consistent with other findings based on EEG and fMRI. Based on the spatiotemporal sources estimated from DeepBraiNNet, we constructed MI related cortical neural networks, which clearly exhibited strong contralateral network patterns for the two MI tasks. Consequently, DeepBraiNNet may provide an alternative way different from the conventional approaches for spatiotemporal EEG source imaging.

EEG Functional Connectivity and Cognitive Variables in Premanifest and Manifest Huntington's Disease: EEG Low-Resolution Brain Electromagnetic Tomography (LORETA) Study

Background

Scientific literature does not offer sufficient data on electroencephalography (EEG) functional connectivity and its correlations with clinical and cognitive features in premanifest and manifest HD.

Aim

This study tries to identify abnormal EEG patterns of functional connectivity, in conditions of “brain resting state” and correlations with motor decline and cognitive variable in Huntington’s disease (HD), in premanifest and manifest phase, looking for a reliable marker measuring disease progression.

Method

This was an observational cross-sectional study; 105 subjects with age ≥18 years submitted to HD genetic test. Each subject underwent a neurological, psychiatric, and cognitive assessment, EEG recording and genetic investigation for detecting the expansion of the CAG trait. EEG connectivity analysis was performed by means of exact Low Resolution Electric Tomography (eLORETA) in 18 premanifest HD (pHD), 49 manifest HD (mHD), and 38 control (C) subjects.

Results

HD patients showed a Power Spectral Density reduced in the alpha range and increased in delta band compared to controls; no difference was detectable between pHD and mHD; the Global Connectivity in pHD revealed no significant differences if compared to mHD. The Current Source Density was similar among groups. No statistically significant results when comparing pHD with C group, even in comparison of mHD with Controls, and pHD with mHD. mHD compared to Controls showed a significant increase in delta, alpha1, alpha2, beta2, and beta3. Lagged Phase Synchronization in delta, alpha1, alpha2, beta2, and beta3 bands was increased in HD compared to controls (t = −3.921, p < 0.05). A significant correlation was found in Regression Analysis: statistically significant results in pHD for the “Symbol Digit Modality Test and lagged phase synchronization” in the Beta1 (r = −0.806, p < 0.05) in the prefrontal regions. The same correlation was found in mHD for the Stroop Word Reading Test (SWRT) in the Alpha2 band (r = −0.759, p < 0.05).

Conclusion

Increased phase synchronization in main bands characterized EEG in HD patients, as compared to controls. pHD were not dissimilar from mHD as regard to this EEG pattern. Increased phase synchronization correlated to cognitive decline in HD patients, with a similar trend in pHD, suggesting that it would be a potential biomarker of early phenotypical expression.

Brain reactions to the use of sensorized hand prosthesis in amputees

OBJECTIVE

We investigated for the first time the presence of chronic changes in the functional organization of sensorimotor brain areas induced by prolonged training with a bidirectional hand prosthesis.

METHODS

A multimodal neurophysiological and neuroimaging evaluation of brain functional changes occurring during training in five consecutive amputees participating to experimental trials with robotic hands over a period of 10 years was carried out. In particular, modifications to the functional anatomy of sensorimotor brain areas under resting conditions were explored in order to check for eventual changes with respect to baseline.

RESULTS

Full evidence is provided to demonstrate brain functional changes, and some of them in both the hemispheres and others restricted to the hemisphere contralateral to the amputation/prosthetic hand.

CONCLUSIONS

The study describes a unique experimental experience showing that brain reactions to the prolonged use of an artificial hand can be tracked for a tailored approach to a fully embedded artificial upper limb for future chronic uses in daily activities.

Neurophysiological Hallmarks of Neurodegenerative Cognitive Decline: The Study of Brain Connectivity as A Biomarker of Early Dementia

Neurodegenerative processes of various types of dementia start years before symptoms, but the presence of a "neural reserve", which continuously feeds and supports neuroplastic mechanisms, helps the aging brain to preserve most of its functions within the "normality" frame. Mild cognitive impairment (MCI) is an intermediate stage between dementia and normal brain aging. About 50% of MCI subjects are already in a stage that is prodromal-to-dementia and during the following 3 to 5 years will develop clinically evident symptoms, while the other 50% remains at MCI or returns to normal. If the risk factors favoring degenerative mechanisms are modified during early stages (i.e., in the prodromal), the degenerative process and the loss of abilities in daily living activities will be delayed. It is therefore extremely important to have biomarkers able to identify-in association with neuropsychological tests-prodromal-to-dementia MCI subjects as early as possible. MCI is a large (i.e., several million in EU) and substantially healthy population; therefore, biomarkers should be financially affordable, largely available and non-invasive, but still accurate in their diagnostic prediction. Neurodegeneration initially affects synaptic transmission and brain connectivity; methods exploring them would represent a 1st line screening. Neurophysiological techniques able to evaluate mechanisms of synaptic function and brain connectivity are attracting general interest and are described here. Results are quite encouraging and suggest that by the application of artificial intelligence (i.e., learning-machine), neurophysiological techniques represent valid biomarkers for screening campaigns of the MCI population.

Electrophysiological correlates of top-down attentional modulation in olfaction

The capacity to pay attention is important for the cognitive ability, for example, evaluating an object for its qualities. Attention can selectively prioritize the neural processes that are relevant to a given task. Neuroimaging investigations on human attention are primarily focused on vision to the exclusion of other sensory systems, particularly olfaction. Neural underpinnings of human olfactory attention are still not clearly understood. Here, we combined electroencephalographic measurements of olfactory event related potential with electrical neuroimaging to investigate how the neural responses after inhaling the same odor differ between conditions with varying levels of attention, and, in which brain areas. We examined the neural responses when participants attended to a rose-like odor of phenylethyl alcohol for evaluating its pleasantness versus its passive inhalation. Our results gathered significant evidence for attentional modulation of the olfactory neural response. The most prominent effect was found for the late positive component, P3, of olfactory event related potential within a second from the odor onset. The source reconstruction of this data revealed activations in a distributed network of brain regions predominantly in inferior frontal cortex, insula, and  inferior temporal gyrus. These results suggest that the neuronal modulations from attention to olfactory pleasantness may be subserved by this network.

Sparse EEG Source Localization Using LAPPS: Least Absolute l-P (0 < p < 1) Penalized Solution

OBJECTIVE

The electroencephalographic (EEG) inverse problem is ill-posed owing to the electromagnetism Helmholtz theorem and since there are fewer observations than the unknown variables. Apart from the strong background activities (ongoing EEG), evoked EEG is also inevitably contaminated by strong outliers caused by head movements or ocular movements during recordings.

METHODS

Considering the sparse activations during high cognitive processing, we propose a novel robust EEG source imaging algorithm, LAPPS (Least Absolute -P (0 < p < 1) Penalized Solution), which employs the -loss for the residual error to alleviate the effect of outliers and another -penalty norm (p=0.5) to obtain sparse sources while suppressing Gaussian noise in EEG recordings. The resulting optimization problem is solved using a modified ADMM algorithm.

RESULTS

Simulation study was performed to recover sparse signals of randomly selected sources using LAPPS and various methods commonly used for EEG source imaging including WMNE, -norm, sLORETA and FOCUSS solution. The simulation comparison quantitatively demonstrates that LAPPS obtained the best performances in all the conducted simulations for various dipoles configurations under various SNRs on a realistic head model. Moreover, in the localization of brain neural generators in a real visual oddball experiment, LAPPS obtained sparse activations consistent with previous findings revealed by EEG and fMRI.

CONCLUSION

This study demonstrates a potentially useful sparse method for EEG source imaging, creating a platform for investigating the brain neural generators.

SIGNIFICANCE

This method alleviates the effect of noise and recovers sparse sources while maintaining a low computational complexity due to the cheap matrix-vector multiplication.

Cortical sources of resting state electroencephalographic rhythms probe brain function in naïve HIV individuals

OBJECTIVE

Here we evaluated the hypothesis that resting state electroencephalographic (EEG) cortical sources correlated with cognitive functions and discriminated asymptomatic treatment-naïve HIV subjects (no AIDS).

METHODS

EEG, clinical, and neuropsychological data were collected in 103 treatment-naïve HIV subjects (88 males; mean age 39.8 years ± 1.1 standard error of the mean, SE). An age-matched group of 70 cognitively normal and HIV-negative (Healthy; 56 males; 39.0 years ± 2.0 SE) subjects, selected from a local university archive, was used for control purposes. LORETA freeware was used for EEG source estimation in fronto-central, temporal, and parieto-occipital regions of interest.

RESULTS

Widespread sources of delta (<4 Hz) and alpha (8-12 Hz) rhythms were abnormal in the treatment-naïve HIV group. Fronto-central delta source activity showed a slight but significant (p < 0.05, corrected) negative correlation with verbal and semantic test scores. So did parieto-occipital delta/alpha source ratio with memory and composite cognitive scores. These sources allowed a moderate classification accuracy between HIV and control individuals (area under the ROC curves of 70-75%).

CONCLUSIONS

Regional EEG abnormalities in quiet wakefulness characterized treatment-naïve HIV subjects at the individual level.

SIGNIFICANCE

This EEG approach may contribute to the management of treatment-naïve HIV subjects at risk of cognitive deficits.

Gamma oscillatory activity is impaired in episodic memory encoding with age

The present study proposes to investigate age-related episodic memory impairment in encoding. We collected ERPs in young and old participants performing a word-encoding task. For subsequently remembered words, young adults had greater activity at the left and anterior electrode sites, whereas old adults had greater posterior activity. Performance correlated positively with central sites in young adults but with left parietal hemisphere activity in old adults. Plus, a large left frontoparietal network increased its activity during the successful encoding for the Beta (13-30 Hz) and Gamma (30-100 Hz) bands in young adults. Old adults had increased activity in the right posterior parietal region for forgotten words in the Gamma band. Using a source localization analysis, we found that age leads to a decrease in Gamma band cerebral activity during encoding of words in the left hemisphere and the bilateral parahippocampal regions. These findings indicate that encoding impairment with age may be associated with dysfunctional Gamma oscillatory activity across a widespread network of left cortical regions.

Brain and cognitive functions in two groups of naïve HIV patients selected for a different plan of antiretroviral therapy: A qEEG study

OBJECTIVE

Cortical sources of electroencephalographic (EEG) rhythms were investigated in two sub-populations of naïve HIV subjects, grouped based on clinical criteria to receive different combination anti-retroviral therapies (cARTs). These EEG sources were hypothesized to reflect beneficial effects of both regimes.

METHODS

Eyes-closed resting state EEG data were collected in 19 (Group A) and 39 (Group B) naïve HIV subjects at baseline (i.e. pre-treatment; T0) and after 5months of cART (T5). Compared with the Group A, the Group B was characterized by slightly worse serological parameters and higher cardiovascular risk. At T0, mean viral load (VL) and CD4 count were 87,694copies/ml and 435cells/μl in the Group A and 187,370copies/ml and 331cells/μl in the Group B. The EEG data were also collected in 50 matched control HIV-negative subjects. Cortical EEG sources were assessed by LORETA software.

RESULTS

Compared to the Control Group, the HIV Groups showed lower alpha (8-12Hz) source activity at T0 while the Group B also exhibited higher delta source activity. The treatment partially normalized alpha and delta source activity in the Group A and B, respectively, in association with improved VL, CD4, and cognitive functions.

CONCLUSIONS

Different cART regimens induced diverse beneficial effects in delta or alpha source activity in the two naïve HIV Groups.

SIGNIFICANCE

These sources might unveil different neurophysiological effects of diverse cART on brain function in naïve HIV Groups as a function of clinical status and/or therapeutic compounds.

Antiretroviral therapy affects the z-score index of deviant cortical EEG rhythms in naïve HIV individuals

OBJECTIVE

Here we tested the effect of combined antiretroviral therapy (cART) on deviant electroencephalographic (EEG) source activity in treatment-naïve HIV individuals.

METHODS

Resting state eyes-closed EEG data were recorded before and after 5 months of cART in 48 male HIV subjects, who were naïve at the study start. The EEG data were also recorded in 59 age- and sex-matched healthy subjects as a control group. Frequency bands of interest included delta, theta, alpha1, alpha2 and alpha3, based on alpha frequency peak specific to each individual. They also included beta1 (13-20 Hz) and beta2 (20-30 Hz). Low-resolution brain electromagnetic tomography (LORETA) estimated EEG cortical source activity in frontal, central, temporal, parietal, and occipital regions.

RESULTS

Before the therapy, the HIV group showed greater parietal delta source activity and lower spatially diffuse alpha source activity compared to the control group. Thus, the ratio of parietal delta and alpha3 source activity served as an EEG marker. The z-score showed a statistically deviant EEG marker (EEG +) in 50% of the HIV individuals before therapy (p < 0.05). After 5 months of cART, delta source activity decreased, and alpha3 source activity increased in the HIV subjects with EEG + (about 50% of them showed a normalized EEG marker).

CONCLUSIONS

This procedure detected a deviant EEG marker before therapy and its post-therapy normalization in naïve HIV single individuals.

SIGNIFICANCE

The parietal delta/alpha3 EEG marker may be used to monitor cART effects on brain function in such individuals.

Abnormal cortical sources of resting state electroencephalographic rhythms in single treatment-naïve HIV individuals: A statistical z-score index

OBJECTIVE

This study tested a simple statistical procedure to recognize single treatment-naïve HIV individuals having abnormal cortical sources of resting state delta (<4 Hz) and alpha (8-13 Hz) electroencephalographic (EEG) rhythms with reference to a control group of sex-, age-, and education-matched healthy individuals. Compared to the HIV individuals with a statistically normal EEG marker, those with abnormal values were expected to show worse cognitive status.

METHODS

Resting state eyes-closed EEG data were recorded in 82 treatment-naïve HIV (39.8 ys.±1.2 standard error mean, SE) and 59 age-matched cognitively healthy subjects (39 ys.±2.2 SE). Low-resolution brain electromagnetic tomography (LORETA) estimated delta and alpha sources in frontal, central, temporal, parietal, and occipital cortical regions.

RESULTS

Ratio of the activity of parietal delta and high-frequency alpha sources (EEG marker) showed the maximum difference between the healthy and the treatment-naïve HIV group. Z-score of the EEG marker was statistically abnormal in 47.6% of treatment-naïve HIV individuals with reference to the healthy group (p<0.05). Compared to the HIV individuals with a statistically normal EEG marker, those with abnormal values exhibited lower mini mental state evaluation (MMSE) score, higher CD4 count, and lower viral load (p<0.05).

CONCLUSIONS

This statistical procedure permitted for the first time to identify single treatment-naïve HIV individuals having abnormal EEG activity.

SIGNIFICANCE

This procedure might enrich the detection and monitoring of effects of HIV on brain function in single treatment-naïve HIV individuals.

Cortical sources of resting state electroencephalographic rhythms differ in relapsing-remitting and secondary progressive multiple sclerosis

OBJECTIVE

Resting state electroencephalographic (EEG) rhythms are abnormal in multiple sclerosis (MS) patients, but it is unclear if they can reflect different neurophysiologic abnormalities in MS sub-types (phenotypes) such as relapsing-remitting (RR) and secondary progressive (SP).

METHODS

We tested whether cortical sources of resting state EEG rhythms are abnormal in MS patients and differ between MS phenotypes. Resting state eyes-closed EEG activity was recorded in 36 RR, 23 SP, and 41 matched healthy subjects. EEG bands of interest were individually identified based on Transition frequency (TF), Individual alpha frequency (IAF), and Individual beta frequency (IBF). LORETA freeware estimated cortical EEG sources.

RESULTS

Widespread TF -4Hz (delta) and IAF (alpha) cortical sources were abnormal in the MS sub-groups compared to the control group. Furthermore, TF -4Hz sources in central, parietal, and limbic regions were higher in amplitude in the SP compared to the RR sub-group.

CONCLUSION

Cortical sources of resting state EEG rhythms are abnormal in MS patients at group level and differ between RR and SP sub-groups.

SIGNIFICANCE

Future studies should test the utility of these EEG markers in the diagnosis and management of MS clinical phenotypes and in the therapy evaluation.

Resting state Rolandic mu rhythms are related to activity of sympathetic component of autonomic nervous system in healthy humans

We tested the hypothesis of a relationship between heart rate variability (HRV) and Rolandic mu rhythms in relaxed condition of resting state. Resting state eyes-closed electroencephalographic (EEG) and electrocardiographic (ECG) data were recorded (10-20 System) in 42 healthy adults. EEG rhythms of interest were high-frequency alpha (10.5-13Hz) and low-frequency beta (13-20Hz), which are supposed to form Rolandic mu rhythms. Rolandic and occipital (control) EEG sources were estimated by LORETA software. Results showed a statistically significant (p<0.05, corrected) negative correlation across all subjects between Rolandic cortical sources of low-frequency beta rhythms and the low-frequency band power (LF, 0.04-0.15Hz) of tachogram spectrum as an index of HRV. The lower the amplitude of Rolandic sources of low-frequency beta rhythms (as a putative sign of activity of somatomotor cortex), the higher the LF band power of tachogram spectrum (as a putative sign of sympathetic activity). This effect was specific as there was neither a similar correlation between these EEG rhythms and high-frequency band power of tachogram spectrum (as a putative sign of parasympathetic vagal activity) neither between occipital sources of low-frequency beta rhythms (as a putative sign of activity of visual cortex) and LF band power of tachogram spectrum. These results suggest that Rolandic low-frequency beta rhythms are related to sympathetic activity regulating heart rate, as a dynamic neurophysiologic oscillatory mechanism sub-serving the interaction between brain neural populations involved in somatomotor control and brain neural populations regulating ANS signals to heart for on-going homeostatic adaptations.

Occipital sources of resting-state alpha rhythms are related to local gray matter density in subjects with amnesic mild cognitive impairment and Alzheimer's disease

Occipital sources of resting-state electroencephalographic (EEG) alpha rhythms are abnormal, at the group level, in patients with amnesic mild cognitive impairment (MCI) and Alzheimer's disease (AD). Here, we evaluated the hypothesis that amplitude of these occipital sources is related to neurodegeneration in occipital lobe as measured by magnetic resonance imaging. Resting-state eyes-closed EEG rhythms were recorded in 45 healthy elderly (Nold), 100 MCI, and 90 AD subjects. Neurodegeneration of occipital lobe was indexed by weighted averages of gray matter density, estimated from structural MRIs. EEG rhythms of interest were alpha 1 (8-10.5 Hz) and alpha 2 (10.5-13 Hz). EEG cortical sources were estimated by low-resolution brain electromagnetic tomography. Results showed a positive correlation between occipital gray matter density and amplitude of occipital alpha 1 sources in Nold, MCI, and AD subjects as a whole group (r = 0.3, p = 0.000004, N = 235). Furthermore, there was a positive correlation between the amplitude of occipital alpha 1 sources and cognitive status as revealed by Mini Mental State Examination score across all subjects (r = 0.38, p = 0.000001, N = 235). Finally, amplitude of occipital alpha 1 sources allowed a moderate classification of individual Nold and AD subjects (sensitivity: 87.8%; specificity: 66.7%; area under the receiver operating characteristic curve: 0.81). These results suggest that the amplitude of occipital sources of resting-state alpha rhythms is related to AD neurodegeneration in occipital lobe along pathologic aging.

Cortical sources of resting state electroencephalographic alpha rhythms deteriorate across time in subjects with amnesic mild cognitive impairment

Cortical sources of resting state electroencephalographic (EEG) rhythms are abnormal in subjects with mild cognitive impairment (MCI). Here, we tested the hypothesis that these sources in amnesic MCI subjects further deteriorate over 1 year. To this aim, the resting state eyes-closed EEG data were recorded in 54 MCI subjects at baseline (Mini Mental State Examination I = 26.9; standard error [SE], 0.2) and at approximately 1-year follow-up (13.8 months; SE, 0.5; Mini Mental State Examination II = 25.8; SE, 0.2). As a control, EEG recordings were also performed in 45 normal elderly and in 50 mild Alzheimer's disease subjects. EEG rhythms of interest were delta (2-4 Hz), theta (4-8 Hz), alpha1 (8-10.5 Hz), alpha2 (10.5-13 Hz), beta1 (13-20 Hz), and beta2 (20-30 Hz). Cortical EEG sources were estimated using low-resolution brain electromagnetic tomography. Compared with the normal elderly and mild Alzheimer's disease subjects, the MCI subjects were characterized by an intermediate power of posterior alpha1 sources. In the MCI subjects, the follow-up EEG recordings showed a decreased power of posterior alpha1 and alpha2 sources. These results suggest that the resting state EEG alpha sources were sensitive-at least at the group level-to the cognitive decline occurring in the amnesic MCI group over 1 year, and might represent cost-effective, noninvasive and widely available markers to follow amnesic MCI populations in large clinical trials.

MEG source localization using invariance of noise space

We propose INvariance of Noise (INN) space as a novel method for source localization of magnetoencephalography (MEG) data. The method is based on the fact that modulations of source strengths across time change the energy in signal subspace but leave the noise subspace invariant. We compare INN with classical MUSIC, RAP-MUSIC, and beamformer approaches using simulated data while varying signal-to-noise ratios as well as distance and temporal correlation between two sources. We also demonstrate the utility of INN with actual auditory evoked MEG responses in eight subjects. In all cases, INN performed well, especially when the sources were closely spaced, highly correlated, or one source was considerably stronger than the other.

High-resolution Functional Source and Impedance Imaging

Functional imaging has played a significant role in bettering our understanding of mechanisms of brain function and dysfunctions. We review recent research on electrophysiological neuroimaging, multimodal neuroimaging integrating functional MRI with EEG, and our development of magnetoacoustic tomography with magnetic induction for high resolution impedance imaging. Examples from research of our group will be shown to illustrate the concepts. The extensive work being pursued by a number of investigators suggests the promise of functional neuroimaging in imaging neural activity from noninvasive measurements.

Cortical sources of EEG rhythms in congestive heart failure and Alzheimer's disease

INTRODUCTION

The brain needs continuous oxygen supply even in resting-state. Hypoxia enhances resting-state electroencephalographic (EEG) rhythms in the delta range, and reduces those in the alpha range, with a pattern similar to that observed in Alzheimer's disease (AD). Here we tested whether resting-state cortical EEG rhythms in patients with congestive heart failure (CHF), as a model of acute hypoxia, present frequency similarities with AD patients, comparable by cognitive status revealed by the mini mental state examination (MMSE).

METHODS

Eyes-closed EEG data were recorded in 10 CHF patients, 20 AD patients, and 20 healthy elderly subjects (Nold) as controls. LORETA software estimated cortical EEG generators.

RESULTS

Compared to Nold, both AD and CHF groups presented higher delta (2-4Hz) and lower alpha (8-13Hz) temporal sources. The highest delta and lowest alpha sources were observed in CHF subjects. In these subjects, the global amplitude of delta sources correlated with brain natriuretic peptide (BNP) level in the blood, as a marker of disease severity.

CONCLUSIONS

Resting-state delta and alpha rhythms suggest analogies between the effects of acute hypoxia and AD neurodegeneration on the cortical neurons' synchronization.

SIGNIFICANCE

Acute ischemic hypoxia could affect the mechanisms of cortical neural synchronization generating resting state EEG rhythms, inducing the "slowing" of EEG rhythms typically observed in AD patients.

Resting state cortical electroencephalographic rhythms are related to gray matter volume in subjects with mild cognitive impairment and Alzheimer's disease

Cortical gray matter volume and resting state cortical electroencephalographic rhythms are typically abnormal in subjects with amnesic mild cognitive impairment (MCI) and Alzheimer's disease (AD). Here we tested the hypothesis that in amnesic MCI and AD subjects, abnormalities of EEG rhythms are a functional reflection of cortical atrophy across the disease. Eyes-closed resting state EEG data were recorded in 57 healthy elderly (Nold), 102 amnesic MCI, and 108 AD patients. Cortical gray matter volume was indexed by magnetic resonance imaging recorded in the MCI and AD subjects according to Alzheimer's disease neuroimaging initiative project (http://www.adni-info.org/). EEG rhythms of interest were delta (2-4 Hz), theta (4-8 Hz), alpha1 (8-10.5 Hz), alpha2 (10.5-13 Hz), beta1 (13-20 Hz), beta2 (20-30 Hz), and gamma (30-40 Hz). These rhythms were indexed by LORETA. Compared with the Nold, the MCI showed a decrease in amplitude of alpha 1 sources. With respect to the Nold and MCI, the AD showed an amplitude increase of delta sources, along with a strong amplitude reduction of alpha 1 sources. In the MCI and AD subjects as a whole group, the lower the cortical gray matter volume, the higher the delta sources, the lower the alpha 1 sources. The better the score to cognitive tests the higher the gray matter volume, the lower the pathological delta sources, and the higher the alpha sources. These results suggest that in amnesic MCI and AD subjects, abnormalities of resting state cortical EEG rhythms are not epiphenomena but are strictly related to neurodegeneration (atrophy of cortical gray matter) and cognition.

Cortical sources of resting state electroencephalographic rhythms in Parkinson's disease related dementia and Alzheimer's disease

OBJECTIVE

Here we test the hypothesis that cortical source mapping of resting state electroencephalographic (EEG) rhythms could characterize neurodegenerative disorders inducing cognitive impairment such as Parkinson's disease related dementia (PDD) and Alzheimer's disease (AD).

METHODS

To address this issue, eyes-closed resting state EEG rhythms were recorded in 13 PDD, 20 AD, and 20 normal elderly (Nold) subjects. Age, gender, and education were carefully matched across the three groups. Mini Mental State Evaluation (MMSE) score probed subjects' global cognitive status, and was matched between the PDD and AD groups. EEG rhythms of interest were delta (2-4 Hz), theta (4-8 Hz), alpha1 (8-10.5 Hz), alpha2 (10.5-13 Hz), beta1 (13-20 Hz), and beta2 (20-30 Hz). EEG cortical sources were estimated by low resolution brain electromagnetic source tomography (LORETA).

RESULTS

With respect to the Nold and AD groups, the PPD group was characterized by peculiar abnormalities of central delta sources and posterior cortical sources of theta and beta1 rhythms. With respect to the Nold group, the PDD and AD groups mainly pointed to lower posterior cortical sources of alpha1 rhythms, which were positively correlated to MMSE score across all PDD and AD subjects as a whole (the lower the alpha sources, the lower the MMSE score). This alpha decrease was greater in the AD than PPD patients.

CONCLUSIONS

The results suggest that topography and frequency of eyes-closed resting state cortical EEG rhythms distinguished PDD and AD groups.

SIGNIFICANCE

We report the existence of different effects of neurodegeneration on the cortical neural synchronization mechanisms generating resting state EEG rhythms in PDD and AD patients.

Cortical responses to consciousness of schematic emotional facial expressions: a high-resolution EEG study

Is conscious perception of emotional face expression related to enhanced cortical responses? Electroencephalographic data (112 channels) were recorded in 15 normal adults during the presentation of cue stimuli with neutral, happy or sad schematic faces (duration: "threshold time" inducing about 50% of correct recognitions), masking stimuli (2 s), and go stimuli with happy or sad schematic faces (0.5 s). The subjects clicked left (right) mouse button in response to go stimuli with happy (sad) faces. After the response, they said "seen" or "not seen" with reference to previous cue stimulus. Electroencephalographic data formed visual event-related potentials (ERPs). Cortical sources of ERPs were estimated by LORETA software. Reaction time to go stimuli was generally shorter during "seen" than "not seen" trials, possibly due to covert attention and awareness. The cue stimuli evoked four ERP components (posterior N100, N170, P200, and P300), which had similar peak latency in the "not seen" and "seen" ERPs. Only N170 amplitude showed differences in amplitude in the "seen" versus "not seen" ERPs. Compared to the "not seen" ERPs, the "seen" ones showed prefrontal, premotor, and posterior parietal sources of N170 higher in amplitude with the sad cue stimuli and lower in amplitude with the neutral and happy cue stimuli. These results suggest that nonconscious and conscious processing of schematic emotional facial expressions shares a similar temporal evolution of cortical activity, and conscious processing induces an early enhancement of bilateral cortical activity for the schematic sad facial expressions (N170).

Resting state cortical electroencephalographic rhythms in subjects with normal and abnormal body weight

It is well known that resting state regional cerebral blood flow is abnormal in obese when compared to normal-weight subjects but the underlying neurophysiological mechanisms are poorly known. To address this issue, we tested the hypothesis that amplitude of resting state cortical electroencephalographic (EEG) rhythms differ among underweight, normal-weight, and overweight/obese subjects as a reflection of the relationship between cortical neural synchronization and regulation of body weight. Eyes-closed resting state EEG data were recorded in 16 underweight subjects, 25 normal-weight subjects, and 18 overweight/obese subjects. All subjects were psychophysically healthy (no eating disorders or major psychopathologies). EEG rhythms of interest were delta (2-4Hz), theta (4-8Hz), alpha 1 (8-10.5Hz), alpha 2 (10.5-13Hz), beta 1 (13-20Hz), beta 2 (20-30Hz), and gamma (30-40Hz). EEG cortical sources were estimated by low-resolution brain electromagnetic tomography (LORETA). Statistical results showed that parietal and temporal alpha 1 sources fitted the pattern underweight>normal-weight>overweight/obese (p<0.004), whereas occipital alpha 1 sources fitted the pattern normal-weight>underweight>overweight/obese (p<0.00003). Furthermore, amplitude of the parietal, occipital, and temporal alpha 2 sources was stronger in the normal-weight subjects than in the underweight and overweight/obese subjects (p<0.0007). These results suggest that abnormal weight in healthy overweight/obese subjects is related to abnormal cortical neural synchronization at the basis of resting state alpha rhythms and fluctuation of global brain arousal.

Region-based current-source reconstruction for the inverse EEG problem

This paper presents a new method for the reconstruction of current sources for the electroencephalography (EEG) inverse problem, which produces reconstructed sources, which are confined to a few anatomical regions. The method is based on a partition of the gray matter into a set of regions, and in the construction of a simple linear model for the potential produced by feasible source configurations inside each one of these regions. The proposed method computes the solution in two stages: in the first one, a subset of active regions is found so that the combined potentials produced by sources inside them approximate the measured potential data. In the second stage, a detailed reconstruction of the current sources inside each active region is performed. Experimental results with synthetic data are presented, which show that the proposed scheme is fast, computationally efficient and robust to noise, producing results that are competitive with other published methods, especially when the current sources are effectively distributed in few anatomical regions. The proposed method is also validated with real data from an experiment with visual evoked potentials.

Resting state cortical rhythms in athletes: a high-resolution EEG study

The present electroencephalographic (EEG) study tested the working hypothesis that the amplitude of resting state cortical EEG rhythms (especially alpha, 8-12 Hz) was higher in elite athletes compared with amateur athletes and non-athletes, as a reflection of the efficiency of underlying back-ground neural synchronization mechanisms. Eyes closed resting state EEG data were recorded in 16 elite karate athletes, 20 amateur karate athletes, and 25 non-athletes. The EEG rhythms of interest were delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-13 Hz), beta 1 (13-20 Hz), and beta 2 (20-30 Hz). EEG cortical sources were estimated by low-resolution brain electromagnetic tomography (LORETA). Statistical results showed that the amplitude of parietal and occipital alpha 1 sources was significantly higher in the elite karate athletes than in the non-athletes and karate amateur athletes. Similar results were observed in parietal and occipital delta sources as well as in occipital theta sources. Finally, a control confirmatory experiment showed that the amplitude of parietal and occipital delta and alpha 1 sources was stronger in 8 elite rhythmic gymnasts compared with 14 non-athletes. These results supported the hypothesis that cortical neural synchronization at the basis of eyes-closed resting state EEG rhythms is enhanced in elite athletes than in control subjects.

Neuroelectric source imaging using 3SCO: a space coding algorithm based on particle swarm optimization and l0 norm constraint

The electroencephalogram (EEG) neuroelectric sources inverse problem is usually underdetermined and lacks a unique solution, which is due to both the electromagnetism Helmholtz theorem and the fact that there are fewer observations than the unknown variables. One potential choice to tackle this issue is to solve the underdetermined system for a sparse solution. Aiming to the sparse solution, a novel algorithm termed 3SCO (Solution Space Sparse Coding Optimization) is presented in this paper. In 3SCO, after the solution space is coded with some particles, the particle-coded space is compressed by the evolution of particle swarm optimization algorithm, where an l0 constrained fitness function is introduced to guarantee the selection of a suitable sparse solution for the underdetermined system. 3SCO was first tested by localizing simulated EEG sources with different configurations on a realistic head model, and the comparisons with minimum norm (MN), LORETA (low resolution electromagnetic tomography), l1 norm solution and FOCUSS (focal underdetermined system solver) confirmed that a good sparse solution for EEG source imaging could be achieved with 3SCO. Finally, 3SCO was applied to localize the neuroelectric sources in a visual stimuli related experiment and the localized areas were basically consistent with those reported in previous studies.

White-matter lesions along the cholinergic tracts are related to cortical sources of EEG rhythms in amnesic mild cognitive impairment

Does impairment of cholinergic systems represent an important factor in the development of amnesic mild cognitive impairment (aMCI), as a preclinical stage of Alzheimer's disease (AD)? Here we tested the hypothesis that electroencephalographic (EEG) rhythms, known to be modulated by the cholinergic system, may be particularly affected in aMCI patients with lesions along the cholinergic white-matter tracts. Eyes-closed resting EEG data were recorded in 28 healthy elderly (Nold) and 57 aMCI patients. Lesions along the cholinergic white-matter tracts were detected with fluid-attenuated inversion recovery sequences on magnetic resonance imaging. The estimation of the cholinergic lesion was performed with a validated semi-automatic algorithm pipeline after registration to a stereotactic template, image integration with stereotactic masks of the cholinergic tracts, and normalization to intracranial volume. The aMCI patients were divided into two groups of high (MCI Ch+; N = 29; MMSE = 26.2) and low cholinergic damage (MCI Ch-; N = 28; MMSE = 26.6). EEG rhythms of interest were delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-13 Hz), beta 1 (13-20 Hz), and beta 2 (20-30 Hz). Cortical EEG generators were estimated by LORETA software. As main results, (i) power of occipital, parietal, temporal, and limbic alpha 1 sources was maximum in Nold, intermediate in MCI Ch-, and low in MCI Ch+ patients; (ii) the same trend was true in theta sources. These results are consistent with the hypothesis that damage to the cholinergic system is associated with alterations of EEG sources in aMCI subjects.

Ibuprofen treatment modifies cortical sources of EEG rhythms in mild Alzheimer's disease

OBJECTIVE

Non-steroidal anti-inflammatory drugs such as ibuprofen have a protective role on risk of Alzheimer's disease (AD). Here we evaluated the hypothesis that long-term ibuprofen treatment affects cortical sources of resting electroencephalographic (EEG) rhythms in mild AD patients.

METHODS

Twenty-three AD patients (13 treated AD IBUPROFEN; 10 untreated AD PLACEBO) were enrolled. Resting EEG data were recorded before and 1 year after the ibuprofen/placebo treatment. EEG rhythms were delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-13 Hz), beta 1 (13-20 Hz), and beta 2 (20-30 Hz). LORETA was used for EEG source analysis.

RESULTS

In the AD PLACEBO group, amplitude of delta sources was globally greater at follow-up than baseline. Instead, amplitude of delta sources remained stable or decreased in the majority of the AD IBUPROFEN patients. Clinical (CDR) but not global cognitive status (MMSE) reflected EEG results.

CONCLUSIONS

These results suggest that in mild AD patients, a long-term ibuprofen treatment slightly slows down the progressive increment of delta rhythms as a sign of contrast against the neurodegenerative processes.

SIGNIFICANCE

They motivate future investigations with larger population and extended neuropsychological testing, to study the relationships among ibuprofen treatment, delta cortical sources, and higher order functions.

Equivalent charge source model based iterative maximum neighbor weight for sparse EEG source localization

How to localize the neural electric activities within brain effectively and precisely from the scalp electroencephalogram (EEG) recordings is a critical issue for current study in clinical neurology and cognitive neuroscience. In this paper, based on the charge source model and the iterative re-weighted strategy, proposed is a new maximum neighbor weight based iterative sparse source imaging method, termed as CMOSS (Charge source model based Maximum neighbOr weight Sparse Solution). Different from the weight used in focal underdetermined system solver (FOCUSS) where the weight for each point in the discrete solution space is independently updated in iterations, the new designed weight for each point in each iteration is determined by the source solution of the last iteration at both the point and its neighbors. Using such a new weight, the next iteration may have a bigger chance to rectify the local source location bias existed in the previous iteration solution. The simulation studies with comparison to FOCUSS and LORETA for various source configurations were conducted on a realistic 3-shell head model, and the results confirmed the validation of CMOSS for sparse EEG source localization. Finally, CMOSS was applied to localize sources elicited in a visual stimuli experiment, and the result was consistent with those source areas involved in visual processing reported in previous studies.

The neural networks involved in pitch labeling of absolute pitch musicians

Investigating the neural substrates of auditory processing of absolute pitch musicians has relevance for understanding the capabilities of the human brain for plasticity. Electroencephalography was used to examine the N1 of auditory-evoked potentials from absolute pitch musicians, nonabsolute pitch musicians, and nonmusicians during tone labeling tasks with and without presentation of a reference tone. Source localization using low-resolution electromagnetic tomography revealed that when labeling tones without a reference, absolute pitch musicians generated greater activity than nonabsolute pitch musicians in the left and right hemispheres. This suggests that when required to label tones without an external reference, absolute pitch musicians have the ability to recruit a greater network than nonabsolute pitch musicians or nonmusicians.

White-matter vascular lesions correlate with alpha EEG sources in mild cognitive impairment

It is an open issue if vascular and Alzheimer's disease (AD) lesions represent additive factors in the development of mild cognitive impairment (MCI), as a preclinical stage of Alzheimer's disease (AD) at group level. In the present study, we tested the hypothesis that electroencephalographic (EEG) alpha rhythms, which are affected (i.e. decreased in amplitude) by AD processes, are relatively preserved in MCI subjects in whom the cognitive decline is mainly explained by white-matter vascular load. Resting EEG was recorded in 40 healthy elderly (Nold), 80 MCI, and 40 AD subjects. In the MCI subjects, white-matter vascular load was quantified based on MRI (0-30 Wahlund visual rating scale). EEG rhythms of interest were delta (2-4Hz), theta (4-8Hz), alpha 1 (8-10.5Hz), alpha 2 (10.5-13Hz), beta 1 (13-20Hz), and beta 2 (20-30Hz). Low resolution electromagnetic source tomography (LORETA) was used for EEG source analysis. As expected, we observed that alpha 1 sources in parietal, occipital, and temporal areas were lower in amplitude in the AD and MCI subjects than in the Nold subjects, whereas the amplitude of wide delta sources was higher in the AD than in the Nold and MCI subjects. As novel results, the amplitude of parietal, occipital, and temporal alpha 1 sources was higher in the MCI V+ (high vascular load; N=42; MMSE=26) than MCI V- group (low vascular load; N=37; MMSE=26.7). Furthermore, a weak but significant (p<0.05) positive statistical correlation was found between the parietal alpha 1 sources and the score of Wahlund scale across all MCI subjects (i.e. the more severe white-matter lesions, the higher parietal alpha source power). The present results are in line with the additive model of cognitive impairment postulating that this arises as the sum of neurodegenerative and cerebrovascular lesions.

Lp norm iterative sparse solution for EEG source Localization

How to localize the neural electric activities effectively and precisely from the scalp EEG recordings is a critical issue for clinical neurology and cognitive neuroscience. In this paper, based on the spatial sparse assumption of brain activities, proposed is a novel iterative EEG source imaging algorithm, Lp norm iterative sparse solution (LPISS). In LPISS, the lp (p < or =1) norm constraint for sparse solution is integrated into the iterative weighted minimum norm solution of the underdetermined EEG inverse problem, and it is the constraint and the iteratively renewed weight that forces the inverse problem to converge to a sparse solution effectively. The conducted simulation studies with comparison to LORETA and FOCUSS for various dipoles configurations confirmed the validation of LPISS for sparse EEG source localization. Finally, LPISS was applied to a real evoked potential collected in a study of inhibition of return (IOR), and the result was consistent with the previously suggested activated areas involved in an IOR process.

A new method of spatio-temporal topographic mapping by correlation coefficient of K-means cluster

It would be of the utmost interest to map correlated sources in the working human brain by Event-Related Potentials (ERPs). This work is to develop a new method to map correlated neural sources based on the time courses of the scalp ERPs waveforms. The ERP data are classified first by k-means cluster analysis, and then the Correlation Coefficients (CC) between the original data of each electrode channel and the time course of each cluster centroid are calculated and utilized as the mapping variable on the scalp surface. With a normalized 4-concentric-sphere head model with radius 1, the performance of the method is evaluated by simulated data. CC, between simulated four sources (s (1)-s (4)) and the estimated cluster centroids (c (1)-c (4)), and the distances (Ds), between the scalp projection points of the s (1)-s (4) and that of the c (1)-c (4), are utilized as the evaluation indexes. Applied to four sources with two of them partially correlated (with maximum mutual CC = 0.4892), CC (Ds) between s (1)-s (4) and c (1)-c (4) are larger (smaller) than 0.893 (0.108) for noise levels NSR</= 0.2; Applied to four sources with two of them completely correlated, CC (Ds) between s (1)-s (4) and c (1)-c (4) are larger (smaller) than 0.97367 (0.1898) for a random noise level NSR</= 0.2; Applied to 128, 64 and 32 recording electrodes, CC (Ds) between s (1)-s (4) and c (1)-c (4) are larger (smaller) than 0.9557 (0.4251) for a random noise level NSR = 0.15; And applied to the cases of spatially overlapped scalp activities, CC (Ds) between s (1)-s (4) and c (1)-c (4) are larger (smaller) than 0.9083 (0.4329) for a random noise level NSR = 0.15. Finally, the method successfully decomposed the ERPs collected in a spatial selective attention experiment into three clusters located at left, right occipital and frontal. The estimated vectors of the contra-occipital area demonstrate that attention to the stimulus location produces increased amplitude of the P1 and N1 components over the contra-occipital scalp. The estimated vector in the frontal area displays two large processing negativity waves around 100 ms and 250 ms when subjects are attentive, and there is a small negative wave around 140 ms and a P300 when subjects are unattentive. The results of simulations and real Visual Evoked Potentials (VEPs) data demonstrate the validity of the method in mapping correlated sources. This method may be an objective, heuristic and important tool to study the properties of cerebral, neural networks in cognitive and clinical neurosciences.

Resting EEG sources correlate with attentional span in mild cognitive impairment and Alzheimer's disease

Previous evidence has shown that resting delta and alpha electroencephalographic (EEG) rhythms are abnormal in patients with Alzheimer's disease (AD) and its potential preclinical stage (mild cognitive impairment, MCI). Here, we tested the hypothesis that these EEG rhythms are correlated with memory and attention in the continuum across MCI and AD. Resting eyes-closed EEG data were recorded in 34 MCI and 53 AD subjects. EEG rhythms of interest were delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-13 Hz), beta 1 (13-20 Hz), and beta 2 (20-30 Hz). EEG cortical sources were estimated by low-resolution brain electromagnetic tomography (LORETA). These sources were correlated with neuropsychological measures such as Rey list immediate recall (word short-term memory), Rey list delayed recall (word medium-term memory), Digit span forward (immediate memory for digits probing focused attention), and Corsi span forward (visuo-spatial immediate memory probing focused attention). A statistically significant negative correlation (Bonferroni corrected, P < 0.05) was observed between Corsi span forward score and amplitude of occipital or temporal delta sources across MCI and AD subjects. Furthermore, a positive correlation was shown between Digit span forward score and occipital alpha 1 sources (Bonferroni corrected, P < 0.05). These results suggest that cortical sources of resting delta and alpha rhythms correlate with neuropsychological measures of immediate memory based on focused attention in the continuum of MCI and AD subjects.

Cortical sources of awake scalp EEG in eating disorders

OBJECTIVE

To investigate quantitative EEG (qEEG) in anorexia nervosa (AN) and bulimia nervosa (BN) in comparison with healthy controls.

METHODS

Resting EEG was recorded in 30 healthy females (age: 27.1+/-5.5), 16-AN females (age: 26.4+/-9.5) and 12-BN females (age: 27.0+/-6.3). Cortical EEG sources (delta, theta, alpha 1, alpha 2, beta 1, beta 2) were modeled by LORETA solutions. The statistical analysis was performed considering the factors Group, power Band, and region of interest (central, frontal, parietal, occipital, temporal, limbic).

RESULTS

Alpha 1 sources in central, parietal, occipital and limbic areas showed a greater amplitude in Controls versus AN and BN groups. Alpha 2 sources in parietal, occipital and limbic areas showed a greater amplitude in Controls than in both AN and BN groups. Alpha 1 sources in temporal area showed a greater amplitude in Controls compared to both the BN and AN groups as well as in the BN group compared to AN group. Central alpha 1 source correlated significantly with BMI in patients.

CONCLUSIONS

These results support the hypothesis that eating disorders are related to altered mechanisms of cortical neural synchronization, especially in rolandic alpha rhythms.

SIGNIFICANCE

To our knowledge this is the first study by LORETA able to detect modifications of cortical EEG activity in eating disorders.

Spatio-temporal EEG source localization using a three-dimensional subspace FINE approach in a realistic geometry inhomogeneous head model

The subspace source localization approach, i.e., first principle vectors (FINE), is able to enhance the spatial resolvability and localization accuracy for closely-spaced neural sources from EEG and MEG measurements. Computer simulations were conducted to evaluate the performance of the FINE algorithm in an inhomogeneous realistic geometry head model under a variety of conditions. The source localization abilities of FINE were examined at different cortical regions and at different depths. The present computer simulation results indicate that FINE has enhanced source localization capability, as compared with MUSIC and RAP-MUSIC, when sources are closely spaced, highly noise-contaminated, or inter-correlated. The source localization accuracy of FINE is better, for closely-spaced sources, than MUSIC at various noise levels, i.e., signal-to-noise ratio (SNR) from 6 dB to 16 dB, and RAP-MUSIC at relatively low noise levels, i.e., 6 dB to 12 dB. The FINE approach has been further applied to localize brain sources of motor potentials, obtained during the finger tapping tasks in a human subject. The experimental results suggest that the detailed neural activity distribution could be revealed by FINE. The present study suggests that FINE provides enhanced performance in localizing multiple closely spaced, and inter-correlated sources under low SNR, and may become an important alternative to brain source localization from EEG or MEG.

Genotype (cystatin C) and EEG phenotype in Alzheimer disease and mild cognitive impairment: A multicentric study

Previous findings demonstrated that haplotype B of CST3, the gene coding for cystatin C, is a recessive risk factor for late-onset Alzheimer's disease (AD; Finckh, U., von der Kammer, H., Velden, J., Michel, T., Andresen, B., Deng, A., Zhang, J., Muller-Thomsen, T., Zuchowski, K., Menzer, G., Mann, U., Papassotiropoulos, A., Heun, R., Zurdel, J., Holst, F., Benussi, L., Stoppe, G., Reiss, J., Miserez, A.R., Staehelin, H.B., Rebeck, G.W., Hyman, B.T., Binetti, G., Hock, C., Growdon, J.H., Nitsch, R.M., 2000. Genetic association of the cystatin C gene with late-onset Alzheimer disease. Arch. Neurol. 57, 1579-1583). In the present multicentric electroencephalographic (EEG) study, we analyzed the effects of CST3 haplotypes on resting cortical rhythmicity in subjects with AD and mild cognitive impairment (MCI) with the hypothesis that sources of resting EEG rhythms are more impaired in carriers of the CST3 B haplotype than non-carriers. We enrolled a population of 84 MCI subjects (42% with the B haplotype) and 65 AD patients (40% with the B haplotype). Resting eyes-closed EEG data were recorded in all subjects. EEG rhythms of interest were delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-13 Hz), beta 1 (13-20 Hz), and beta 2 (20-30 Hz). EEG cortical sources were estimated by low-resolution brain electromagnetic tomography (LORETA). Results showed that the amplitude of alpha 1 (parietal, occipital, temporal areas) and alpha 2 (occipital area) was statistically lower in CST3 B carriers than non-carriers (P < 0.01). Whereas there was a trend towards statistical significance that amplitude of occipital delta sources was stronger in CST3 B carriers than in non-carriers. This was true for both MCI and AD subjects. The present findings represent the first demonstration of relationships between the AD genetic risk factor CST3 B and global neurophysiological phenotype (i.e., cortical delta and alpha rhythmicity) in MCI and AD subjects, prompting future genotype-EEG phenotype studies for the early prediction of AD conversion in individual MCI subjects.

Apolipoprotein E and alpha brain rhythms in mild cognitive impairment: A multicentric Electroencephalogram study

OBJECTIVE

Relationships between the apolipoprotein E epsilon4 allele and electroencephalographic (EEG) rhythmicity have been demonstrated in Alzheimer's disease (AD) patients but not in the preclinical stage prodromic to it, namely, mild cognitive impairment (MCI). The present multicentric EEG study tested the hypothesis that presence of epsilon4 affects sources of resting EEG rhythms in both MCI and AD subjects.

METHODS

We enrolled 89 MCI subjects (34.8% with epsilon4) and 103 AD patients (50.4% with epsilon4). Resting eyes-closed EEG data were recorded for all subjects. EEG rhythms of interest were delta (2-4 Hz), theta (4-8 Hz), alpha 1 (8-10.5 Hz), alpha 2 (10.5-13Hz), beta 1 (13-20 Hz), and beta 2 (20-30 Hz). EEG cortical sources were estimated by low-resolution brain electromagnetic tomography.

RESULTS

Results showed that amplitude of alpha 1 and 2 sources in occipital, temporal, and limbic areas was lower in subjects carrying the epsilon4 allele than in those not carrying the epsilon4 allele (p < 0.01). This was true for both MCI and AD. For the first time to our knowledge, a relationship was shown between ApoE genotype and global neurophysiological phenotype (ie, cortical alpha rhythmicity) in a preclinical AD condition, MCI, in addition to clinically manifest AD.

INTERPRETATION

Such a demonstration motivates future genotype-EEG phenotype studies for the early prediction of AD conversion in individual MCI subjects.